Potential FPN removal workflow (no NR)

i just thought i missed something of how to work with the bmcc footage

so for now i use the spatial and temporal noise settings when i want too and the sharpen blur functions....

i just thought i missed something of how to work with the bmcc footage

so for now i use the spatial and temporal noise settings when i want too and the sharpen blur functions....

Spacial and temporal noise reduction are different to fixed pastern noise and not really required for the BMCC. That said, you could probably improve the bmcc's ISO 1600 by making a median dark frame.

ok, if i will shoot in 1600asa ill keep that in mind, thanks!

I've been working on a workflow for removing the FPN from scenes that are not under exposed to begin with. You can view the various other threads on this topic.

I need to hit the sack and will provide more details and examples tomorrow. Bottom line is that I'm seeing improvements to the point where there FPN is essentially invisible for properly exposed scenes and reduced for highly pushed scenes (perhaps more tweaks can provide further improvement here).

In a nutshell I did this:

1) Filmed an out of focus gray card with even 5600k light. I would actually like to redo this with even more even lighting, but my capture is good enough for this test.

2) Converted 100 frames of this footage to 16-bit DPX files using Resolve

3) Loaded 20 files at a time into photoshop layers, converted them to smart objects, and applied 'mean' as the stacking method. I had to break them into 20 file chunks to have enough available RAM.

4) Rasterized these files back down into 16-bit tiff files

5) Took my new files and did steps (3-4) with them again to create a single file that is the average of all sources. Ideally I would do this with even more frames.

The cool thing is that if you stretch the colors in this file, you can really see the FPN pattern of your sensor (will post tomorrow).

6) Now back in resolve I create a layer node with the footage I want to improve and the noise.tiff file. The merging mode is set to subtract.

7) The footage is now too dark, so create a sequential node and apply offset to bring it back up where you want it to be. We are basically subtracting the data from the gray card (which should be very even) plus the fixed pattern from the sensor.

8) Grade as usual

The cool thing is that the pattern seems stable. I'm applying it to footage that I took days ago with nice results.

I also tried this with the lens cap on instead of the gray card without good results. I think that there aren't enough bits down in the deepest blacks to represent what we need.

Ideally this would all be done in camera, but after you have the noise.tiff file it is just a few clicks to get things set. I'm looking forward to seeing if this works in the long run, along with posting samples tomorrow.

Have you been able to play with your FPN removal method lately? Any further findings? I have tried this method with noticeable but limited success and was wondering if this method is a wash for ProRes footage on the BMPC 4K.

Thanks for all the info in the is thread.

For the crosshatch pattern that shows up, I have had some success with this. However I haven't really found it to be much of a problem in my footage so I haven't spent a lot of time with it.

For the vertical bars that show up in the shadows or pushed footage, I have not had any success at all. For one thing the pattern seems to change over time which makes it basically impossible to remove. Subtracting a dark frame just makes the pattern worse. Maybe I am doing something wrong.

From what I remember I've had some success with temporal noise reduction in Resolve for the vertical bars.

Interesting post. Looks promising


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